Analyse Rapide des notes - DS1

import pandas as pd
from ipywidgets import interact, interactive, fixed, interact_manual, IntSlider
# Standard plotly imports
import chart_studio.plotly as py
import plotly.graph_objs as go
from plotly.offline import iplot, init_notebook_mode
# Using plotly + cufflinks in offline mode
import cufflinks as cf
cf.go_offline(connected=False)
init_notebook_mode(connected=False)

Continus - DSC1

df=pd.read_csv("Notes_DSC1.csv", encoding="latin-1")
df.describe()
Note Exo1 Exo2 Exo 3
count 28.000000 28.000000 28.000000 28.000000
mean 12.660714 3.401786 4.026786 5.000000
std 3.609539 1.198648 1.774745 1.635826
min 4.500000 0.750000 0.500000 0.750000
25% 10.625000 3.000000 2.937500 4.437500
50% 13.000000 3.875000 4.250000 5.500000
75% 15.250000 4.250000 5.062500 6.062500
max 18.250000 4.750000 7.250000 7.000000
df['Note']=df["Note"]*100/20
df['Exo1'] = df['Exo1']*100/5
df['Exo2'] = df['Exo2']*100/8
df['Exo 3'] = df['Exo 3']*100/7
df["Note"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo1"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exercice 1 - Calculs matriciel",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo2"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 2 - Géométrie",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo 3"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 3 - Matrices, inversion",xTitle='Notes sur 100', yTitle='Quantité')

Alternants - DSA1

df=pd.read_csv("Notes_DSA1.csv", encoding="latin-1")
df.describe()
Note Exo1 Exo2 Exo 3
count 22.000000 22.000000 22.000000 22.000000
mean 11.681818 2.579545 3.625000 5.340909
std 3.132189 0.853516 1.873611 1.493130
min 6.000000 1.000000 0.000000 1.500000
25% 9.562500 2.125000 2.437500 4.312500
50% 11.750000 2.500000 3.750000 5.500000
75% 13.187500 3.187500 4.437500 6.500000
max 19.000000 4.000000 8.000000 7.000000
df['Note']=df["Note"]*100/20
df['Exo1'] = df['Exo1']*100/5
df['Exo2'] = df['Exo2']*100/8
df['Exo 3'] = df['Exo 3']*100/7
df["Note"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo1"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exercice 1 - Calculs matriciel",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo2"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 2 - Géométrie",xTitle='Notes sur 100', yTitle='Quantité')
df["Exo 3"].iplot(kind="histogram", bins=20, theme="white", title="Répartition des notes - Exo 3 - Matrices, inversion",xTitle='Notes sur 100', yTitle='Quantité')